Accessibility Measures in Modal Choice Models: A Proof of Concept Applied to Freight Transport

Modal choice models applied to interregional or international freight transportation network models are often based on rather coarse origin-destination matrices, containing annual transported tonnages between (sub)regions, for instance. Generally, only basic (sometimes constructed) independent variables (transportation costs or transit times) are used because other variables such as shipment sizes, service frequencies, etc. are not available. Using origin-destination matrices and an assignment model, it is also possible to compute spatial accessibility measures that can further be used as additional explanatory variables. Indeed, several published studies have identified network accessibility as an important element in the mode-choice decision. This paper also shows that the inclusion of an accessibility measure in the utility functions of a logit model substantially improves the performance of a transportation network model, both in the modal choice and the assignment levels of the classical four-step model. Consequently, the assignment of the estimated modal demands results in more accurate estimated traffic on the networks. The model presented in this paper is to be considered as a proof of concept because its workflow should further be streamlined to make it easily useable by modelers.

Calibration and Validation of Strategic Freight Transportation Planning Models with Limited Information

Strategic transportation network models are often used as support tools in the framework of decisions to be taken at the policy level, such as the Trans-European Network projects. These models are mostly setup using aggregated or limited data. If their calibration is regularly mentioned in the literature, their validation is barely discussed. In this paper, several modal choice model specifications that make only use of explanatory variables available at the network level are described and applied to a large scale case. A validation exercise is performed at three levels of aggregation. The paper is designed from a strategic transport planning perspective, and does not present new modal choice formulations or assignment procedures. Its main added value is the focus on calibration and validation considerations. Despite the limited explanatory information used, the global performance of the best models can be considered as satisfactory. However, the quality of the models varies from mode to mode, the use of railway transport being the most difficult to predict without more specific input.

Empirical Analysis of Multiple-Criteria Decision-Making (Mcdm) Process for Freight Transportation Mode Selection

In Ghana, freight transport is growing continuously every year due to its location and business processes. However, road transport carries 86% of freight despite its numerous negative impacts. Hence, the government has invested in rail transport, with 70% of its capacity is for freight transport in her busy freight transport corridor (eastern transport regions of Ghana). Thus, awareness of criteria considered when deciding on freight transport becomes vital. Hence, this study aims to improve the understanding of the factors of freight transport mode selection in Ghana from the decision-making process by identifying criteria that affect their decisions on mode transportation. The combination of Fuzzy AHP and Topsis is used to find the weights and suggest suitable alternatives for the decision-makers in the Eastern transport regions of Ghana. The result of this study shows that the criteria to consider when selecting freight transport mode in the regions are prioritized in other of Transport cost (0.6544), transport Time factors (0.2562), reliability, and flexibility (0.0605), and security, Risk of damage and lose factors (0.0287). Additionally, the suitable mode(s) of transportation in the stated corridor is owned truck carrier transport compared to the railroad, road-barge, and Contracted Carrier, thus, in descending order. The results provide organizations to prioritize these factors when deciding to select freight transport mode. At the same time, the government must remove some inputs that result in high transport costs, enforce policies, and invest in the appropriate mode.

Estimating Elasticities for Freight Transport Using a Network Model: An Applied Methodological Framework

This paper presents a general framework that can be used to estimate direct and cross elasticities for freight transport using a network model. This methodology combines operational research (network assignments in a geographical information system) with more classical econometrics (multinomial logit choice models). The application of the method to a real-world case is illustrated by a simple model that relies on the generalized cost of transport as the only explanatory variable in the utility function. The methodological framework allows, however, for the implementation of more complex functions. Beside the generalized cost functions for road, rail and inland waterways transport, the network model needs origin-destination matrixes and digitized networks. They are imported from ETIS Plus, a European transport policy information system. A set of direct and cross elasticities is presented. The estimated values are obtained using two methods: the first computes standard elasticities, while the second estimates arc elasticities. Figures are presented for Europe and for a large region around the Benelux countries, where more competition exists between the three modes of interest.

Choosing Multimodal Freight Mix: An Integrated Multi-Objective Multicriteria Approach

Multimodal freight transportation emerges as the go-to strategy for cost-effectively and sustainably moving goods over long distances. In a multimodal freight system, where a single contract includes various transportation methods, businesses aiming for economic success must make well-informed decisions about which modes of transport to use. These decisions prioritize secure deliveries, competitive cost advantages, and the minimization of environmental footprints associated with transportation-related pollution. Within the dynamic landscape of logistics innovation, various multicriteria decision-making (MCDM) approaches empower businesses to evaluate freight transport options thoroughly. In this study, we utilize a case study to demonstrate the application of the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) algorithm for MCDM decision-making in freight mode selection. We further enhance the TOPSIS framework by integrating the entropy weight coefficient method. This enhancement aids in assigning precise weights to each criterion involved in mode selection, leading to a more reliable decision-making process. The proposed model provides cost-effective and timely deliveries, minimizing environmental footprint and meeting consumers’ needs. Our findings reveal that freight carbon footprint is the primary concern, followed by freight cost, time sensitivity, and service reliability. The study identifies the combination of Rail/Truck as the ideal mode of transport and containers in flat cars (COFC) as the next best option for the selected case. The proposed algorithm, incorporating the enhanced TOPSIS framework, benefits companies navigating the complexities of multimodal transport. It empowers making more strategic and informed transportation decisions. This demonstration will be increasingly valuable as companies navigate the ever-growing trade within the global supply chains.

Urban Freight Consolidation Model for Post-Hauler Planning

Freight transportation in urban areas has increased significantly in a shorter period due to the widespread use of e-commerce, fast delivery, and population growth. Recently, a noticeable government initiative aimed at creating an effective, acceptable, and sustainable city logistics policy. This paper examines freight consolidation as a transportation strategy for optimizing last-mile delivery costs. Freight consolidation involves combining smaller shipments from various origins into a single, larger shipment for more efficient transportation to a common destination. This approach is particularly beneficial for last-mile delivery, where frequent deliveries of smaller quantities are frequently visible. Finally, we provide an illustrative example targeting urban freight stakeholders for practicing possible consolidation methodology. The result in the illustrative example shows that freight with 3-day consolidation, despite the delay penalty, is cheaper than daily shipping, and both are cheaper than 2-day consolidated shipping. The study will benefit urban businesses and freight services.

Intermodal Freight Network Design for Transport of Perishable Products

The amount of perishable products transported via the existing intermodal freight networks has significantly increased over the last years. Perishable products tend to decay due to a wide range of external factors. Supply chain operations mismanagement causes waste of substantial volumes of perishable products every year. The heretofore proposed mathematical models optimize certain supply chain processes and reduce decay of perishable products, but primarily deal with local production, inventory, distribution, and retailing of perishable products. However, significant quantities of perishable products are delivered from different continents, which shall increase the total transportation time and decay potential of perishable products as compared to local deliveries. This paper proposes a novel optimization model to design the intermodal freight network for both local and long-haul deliveries of perishable products. The objective of the model aims to minimize the total cost associated with transportation and decay of perishable products. A set of piecewise approximations are applied to linearize the non-linear decay function for each perishable product type. CPLEX is used to solve the problem. Comprehensive numerical experiments are conducted using the intermodal freight network for import of the seafood perishable products to the United States to draw important managerial insights. Results demonstrate that increasing product decay cost may significantly change the design of intermodal freight network for transport of perishable products, cause modal shifts and affect the total transportation time and associated costs.

多情景模拟下的跨境铁路运输时效研究——以中老铁路为例

跨境铁路运输是中国与周边国家陆路联通的重要环节。跨境铁路运输时效既受线路畅通情况、基础设施技术等级等“硬联通”因素的制约,也受到海关条例、口岸畅通水平等“软联通”因素的影响。因此,跨境铁路运输时效研究应充分考虑不同情景,以期更科学地模拟运输时长的变化机理。本文以中老铁路(中国昆明−老挝万象,简称中老铁路)为例,在梳理中老铁路沿线地区社会经济概况及基础设施发展水平的基础上,考虑不同运营速度、通关时间、铁轨换装、多式联运等因素,构建了长途跨境运输时间的计算模型,采用多情景模拟方法,解析了中老铁路运的优势距离及客货运时效变化。研究表明:①中老铁路有助于沿线跨境运输时间显著减少。相比公路运输,客货运时间优势均超过20%;②通关时间是影响跨境铁路运输的关键要素之一,占运输总时长的20%~60%;③铁海联运是中老铁路运输进一步提升运输效率的途径,能有效缩短老挝至日本的总运输时间。

基于多目标进化的超限超重货物运输专列路径优化方法

针对超限超重货物运输专列路径优化问题,引入限界改造和桥梁加固要素,以铁路运能损失、运输时间和运输费用的最小化为优化目标,构建铁路超限超重货物运输专列路径优化模型;考虑专列同时运送多件超限超重货物的特点,设计货物综合投影算法,并以Pareto支配关系框架下的NSGA-Ⅱ多目标进化算法为基础,结合基于移动不可行解的自适应惩罚函数的约束处理技术及超限超重货物运输专列开行特征,提出一种基于多目标进化的铁路超限超重货物运输专列路径优化算法。实例分析结果表明:该方法能高效合理地处理路径优化任务中的多个目标;与常用的3种约束多目标算法相比,设计的优化算法能使计算耗时降低0.24%~29.94%、超体积指标值提高4.25%~13.11%,并得到一组收敛性和多样性更好的相对最优方案。该方法克服了传统专列路径优化中单纯依靠经验或从备选方案中择优的弊端,可为铁路超限超重货物运输专列路径决策提供技术支持。

考虑实质性降本的物流成本评价指标及相关对策建议

为科学评判物流成本,提升物流成本评价指标的系统性、全面性,首先,对物流成本、宏观物流成本的概念进行辨析,通过国内外对比、实地调研等方法,深入分析我国物流成本构成、物流发展阶段与水平,并从产业结构、平均运距、运输结构三方面探讨宏观物流成本影响因素;然后,提出单位货物运输周转量支撑GDP产出值、单位货物运输周转量物流成本、物流费用增速与GDP增速之比(或之差)、社会物流总费用占社会物流总额比重等物流成本评价补充指标,从不同维度弥补了“社会物流总费用与GDP的比率”作为物流成本单一宏观评价指标的局限性;最后,基于实质性降本视角,分析制约物流成本的深层原因,并从降低多式联运成本,优化运输组织,加快发展物流领域新质生产力,实现精益化仓储管理,提升供应链一体化管理水平等方面,提出降低物流成本的对策建议。

基于嵌入式技术的无人驾驶货运系统设计

针对目前货运行业人力成本高且效率低的问题,设计一种基于嵌入式技术的无人驾驶货运系统。该系统通过摄像头扫描目标地址即可携带货物自动到达并返回,同时对于复杂货运场合可实现多系统独立工作。设计采用嵌入式芯片STM32F4和串级PID算法,通过K210和OpenMV摄像头模块采集地址和轨迹信息,实现货运系统的自动运送过程。经测试,该系统能准确完成货运任务,反应灵敏,性价比高,可广泛应用于货运场合。

基于多源传感技术的铁路货运智慧监控模拟实验系统设计

在“新工科”教育背景下,为进一步丰富和优化铁路货运实验教学内容,设计了基于多源传感技术的铁路货物运输智慧监控模拟实验系统,即使用多源传感信息技术对货物运输环境和货物运输状态进行监测以及预警。结合OBE教育理念开展教学改革实践,提出提高学生综合能力的教学和评价方法。学生能对铁路货物运输的全过程有更为深刻的认识,提升对货物运输系统的操作能力,为今后从事铁路货运工作打下坚实的基础。

客货共运模式的高铁货运发展空间分析

在铁路运输技术不断改善的背景下,高速铁路的运输条件得到了大力改善,运力也得到了相应增加,货物运输变得更加快捷、安全、可靠。利用高铁开展快捷货物运输可以满足高附加值、高时效要求的快递市场需求。针对该现状,考虑高铁、高速公路和民航之间的货运竞争,在由若干OD形成的货运网络中,以客运动车组预留车厢模式下总运输利润最大为目标,构建基于多目标的客货共运模式的高铁货运双层规划模型,计算货运网络中高铁的运价以及货流量在高铁快运网络中的分布。通过NSGA-Ⅱ多目标优化算法,求出Pareto最优解。最后以京沪间快递运输为例,验证所建模型的有效性。算例结果表明:预留货运车厢模式对于高铁客运的影响较小,可以增加高铁的盈利能力,在一些客运量不足的短途高铁线路上可以开展客货共运模式,以增加高铁收益,增强高铁在短途运输中对于公路货运的竞争力。

基于SARIMA-SVR模型的铁路货运量预测方法

鉴于铁路货运量受多种外部因素影响呈现显著的随机波动特征而难以准确预测,提出了SARIMA-SVR预测模型。首先,对全国铁路月度货运量序列进行季节时间序列(SARIMA)建模,得到模型的初始预测值及预测残差。其次,构建支持向量机(SVR)回归预测模型,将影响铁路货运量的外部因素作为模型输入项,SARIMA模型预测残差序列、月度货运量序列分别作为模型输出项,由此分别获得SARIMA模型预测残差的优化值以及SVR模型的货运量预测值。三是将优化后的SARIMA模型预测残差与其初始预测值相加,得到优化后的SARIMA模型预测值。四是再对优化后的SARIMA模型预测值和SVR模型预测值进行加权求和,得到SARIMA-SVR模型的预测结果。最后,对SARIMA-SVR模型进行消融实验验证模型有效性,并将该模型与经典预测模型进行测算精度对比。结果表明,SARIMA-SVR模型的预测精度优于单一模型和经典预测模型,在货运量预测方面具有良好的适用性。

不确定运价下长江集装箱多式联运路径优化

为充分贴合长江集装箱多式联运场景,在分析长江多式联运组织特点的基础上,考虑不确定运价及不同航段航道通航条件影响,以包含运输周转成本、碳排放成本和时间成本在内的总成本最小化为目标,构建不确定条件下长江集装箱多式联运路径优化模型,并设计蒙特卡洛仿真与改进的狼群算法实现模型求解,最后通过算例分析验证改进的狼群算法的有效性。算例分析结果表明,公路运输能有效控制运输的时间成本,铁路与水路运输在运输经济性与绿色性方面更具优势。在长江航道通航能力与最大中转次数限制下,运输任务将选择较高成本运输方案以满足航道与托运人要求。

福建省沿海港口货运职能识别及结构演变研究

精准识别港口货运职能及其演变规律,是推动港口群协同发展的重要环节。采用货种区位商、货物离散指数、港口分工系数等方法,定量分析福建省沿海港口群货物吞吐量增长态势、货运职能及结构演变趋势。结果表明:2000—2020年,福建省沿海港口群货物吞吐量整体呈增长趋势,但年增长速度趋于放缓;沿海港口群的主要职能以煤炭、钢铁、粮食等传统货物运输为主,其中福州港主要职能最多,具有一定的综合功能;沿海港口群的港口分工系数明显下降,各港间货种结构差异缩小,货运职能特征由单一向多样化转变。今后应优化福建省沿海港口群空间布局,明确港口功能定位,促进沿海港口协同发展。

基于中国东盟货运航线数据的网络结构与鲁棒性

利用复杂网络理论,深入分析中国东盟航空货运网络的鲁棒性。通过构建网络模型,分析网络拓扑结构,识别关键节点,以最大连通子图相对大小、网络效率和平均路径长度为衡量指标进行鲁棒性分析。结果显示,网络在随机攻击模式下的鲁棒性优于蓄意攻击。因此,应对关键节点进行保护,防止其遭受攻击。这些发现对理解和改进网络稳定性和鲁棒性具有重要意义,同时为提升网络效率和可靠性提供了支持。

需求不确定的铁路车流径路优化模型

引入不确定理论中的鲁棒优化描述铁路货运日常运输组织工作中的车流量波动,提出需求不确定的铁路车流径路优化模型。首先,考虑线路通过能力和网络流量守衡约束,以绕道率阈值参数控制车流径路里程的合理性,以走行成本最小化为优化目标,建立需求确定的车流径路优化模型;然后,引入盒式不确定集描述车流量的波动性,设计鲁棒代价调节模型的保守程度,基于鲁棒对等理论建立需求不确定的车流径路优化模型;最后,通过小型算例验证模型的正确性,并基于沈阳铁路局集团有限公司所辖路网的实际算例验证模型的实用性。结果表明:部分车流量发生波动时,对应的最优径路方案随之发生变化;鲁棒代价能够权衡最优方案的成本和违反通过能力约束的概率,小型算例和实际算例中鲁棒代价分别取5和11时,得到的车流径路方案处于系统成本与运输需求满足的平衡点。该模型及鲁棒优化理论可为管理者制定车流径路方案提供决策参考。

货运交通电气化技术的电气化公路方案与氢能方案对比研究

重型货车是我国交通运输行业的高耗能设备和主要的碳排放来源,其柴油年消耗量约占我国柴油年消耗总量的40%、CO_(2)年排放量占交通运输领域CO_(2)年排放总量的50%左右。在“双碳”目标和能源革命的背景下,构建绿色清洁、安全高效的公路货运方式,推进重载货运交通的低碳化和清洁化转型,这已成为一种必然趋势。目前,重型货车电气化主要有充电方案、换电方案、氢能重卡方案以及电气化公路方案。文章主要介绍了氢能重卡方案和电气化公路方案,并基于某运煤专线,通过成本核算,对比分析了二者的经济性和应用场景。分析结果表明,对于固定运输线路的货运交通,当年运量大于204.83万吨时,采用电气化公路方案更具有经济性;当年运量低于204.83万吨时,氢能重卡方案成本则更低。

基于组合权重TOPSIS的超限货物运输方案评价

超限货物运输方案是铁路安全运输超限货物的重要前提和保障。为实现超限货物运输方案的优选,提出一种基于组合权重和TOPSIS法的铁路超限货物运输方案评价模型。从装载加固方案、线路条件、运输组织复杂程度和运输费用4个方面分析超限货物运输方案的影响因素,确定方案评价指标,构建综合评价指标体系。运用博弈论原理计算方案评价指标的组合权重,其中主观权重由G1法确定,客观权重由熵权法确定。运用TOPSIS法对运输方案进行评价,构建基于组合权重和TOPSIS法的超限货物运输方案的综合评价模型。最后给出超限货物运输实例,运用所构建的评价模型对各运输方案进行评价。结果表明,建立的方案评价模型能够科学、合理地对超限货物运输方案进行比选。